Heparan sulfate promotes the aggregation of HDL‐associated serum amyloid A: evidence for a proamyloidogenic histidine molecular switch
Bibliographic record
Abstract
During inflammatory diseases, serum amyloid A (SAA), an acute-phase apolipoprotein of HDL, can assemble into tissue deposits called AA amyloids. The mechanism and physiological factors promoting amyloidosis are largely unknown but likely involve heparan sulfate (HS), a glycosaminoglycan colocalized with all types of amyloids. In this study, we explored HDL-SAA:HS interactions using in vitro and cell culture assays to identify HS-binding domains that promote the conversion of native SAA into AA amyloid. HS causes the remodeling of HDL-SAA at mildly acidic pH, producing SAA-rich aggregates. A sequence motif in SAA responsible for this conversion was identified that contains a pH-sensitive heparin/HS-binding site, functions as a ligand for a cell surface receptor, and acts as a structural focal point for SAA aggregation. Synthetic peptides corresponding to this region promoted the deposition of AA amyloid in a monocyte culture model for AA amyloidogenesis. The effects were peptide sequence specific and reliant on the protonation of H36. We conclude that a highly conserved motif required for SAA binding to macrophages can, under acidic pH conditions and in an HS-dependent manner, also act as a molecular switch, directing SAA misfolding into AA amyloid. Similar histidine-dependent HS-binding sites are also found in other amyloidogenic polypeptides.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".